WEBVTT 00:30.000 --> 00:45.000 Micro Focus, creators of visual programming tools for software development, is pleased to provide major funding for the Computer Chronicles, the story of this continuing evolution. 00:45.000 --> 01:07.000 Welcome to the Computer Chronicles, I'm Stuart Shafae and I'm turning the wrong knob here. This is Gary Kildall and this is Armitron, our noisy little robot here. We're using Armitron to demonstrate some of the basic things that a robot can do. 01:07.000 --> 01:20.000 And even though this is a small toy, it really does demonstrate those things. For example, this robot has a shoulder which can turn along that axis. It can lift by its shoulder or come down. It's got an elbow which it can bend. 01:20.000 --> 01:32.000 It has a wrist which it can move and it has a hand which it can open. And it can actually do something that humans can't do. It can twist its wrist around that particular joint. 01:32.000 --> 01:40.000 Now, Gary, this is a small example of a robot. It's certainly not a computer. How do computers and robotics relate? 01:40.000 --> 01:50.000 Well, there are a whole lot of devices that fall in this category of robots. And they go from the simple show robots all the way up to sophisticated assembly line type of robot. 01:50.000 --> 02:04.000 And in a show robot, for example, there's a human operator that's somehow communicating with this device, making it roll around, giving brochures and things of that sort. But as we add more intelligence on board, then that's where the computer comes into play. 02:04.000 --> 02:09.000 The computer then controls all the devices, makes some on-board decisions based on its own intelligence. 02:09.000 --> 02:18.000 Well, there's been a science fiction fascination with robots throughout this century, but the fictional robots bear little resemblance to today's real robots. 02:18.000 --> 02:25.000 The image of a robot has taken many different forms since the clockwork musicians and dolls of the 18th century. 02:25.000 --> 02:37.000 But during the mechanical age of the early 20th century, the robot became a frightening symbol of the future, threatening to transform the world into an over-mechanized, de-humanized society. 02:37.000 --> 02:46.000 In heavy industries, the worker was becoming an accessory to the machine, repeating the same task hundreds or thousands of times in precisely the same way. 02:46.000 --> 02:54.000 To those not benefiting directly from the new methods, mechanization of work and life called up bleak images of the future. 02:54.000 --> 03:06.000 Fritz Lang's Metropolis depicted the year 2000, a world divided between industrial barons and downtrodden workers, slaves to an underground machine city operating day and night. 03:06.000 --> 03:16.000 The drive for efficiency leads the city's master to consult an inventor who has devised the ultimate tool, a mechanical replacement for the imperfect human being. 03:16.000 --> 03:25.000 This remarkable film may not have been completely accurate in its predictions, but it anticipated a fictional idea of robots that persisted for decades after it. 03:25.000 --> 03:30.000 A human-made, human-like mechanism that behaves like its creator. 03:30.000 --> 03:41.000 More often than not, the machine tended to destroy its creator as well, prompting writer Isaac Asimov in 1947 to devise the first three laws of robotics. 03:41.000 --> 04:00.000 These prescriptions assume either a large degree of intelligence or, interpreted another way, programmed behavior, one of the principal criteria for modern robotic systems. 04:00.000 --> 04:13.000 While not usually designed with human characteristics, post-war robots were, from early on, capable of programmed motion. Servo mechanisms or feedback-controlled robots began to appear in the late 1950s. 04:13.000 --> 04:24.000 From 1960 on, robots became useful adjuncts to a number of industries, particularly in jobs that were uncomfortable or hazardous to humans, like welding and painting. 04:24.000 --> 04:35.000 Repetitive functions as performed by the machine-like humans in Metropolis were being taken over by robots with more human-like capabilities, including sight, touch, and error detection. 04:35.000 --> 04:56.000 In some of the latest applications, CAD-CAM systems work directly with a robot arm to transfer the design of a part from the video screen to the finished product. 04:56.000 --> 05:07.000 Joining us now is Dr. David Knitson, director of the robotics department at SRI International, and Matt Guerreri, who's an executive with Autobotics here in the Silicon Valley. Gary? 05:07.000 --> 05:19.000 David, I guess everybody has the idea that a robot should go around and wash your dishes and clean your house and so forth, but I have a feeling there's a lot more to robotics than that. Can you give us some idea of what's going on in the industry? 05:19.000 --> 05:34.000 Well, industry has been using robotics for 15 years already. These are robots that are designed to do dirty jobs in industry, and they're doing them. 05:34.000 --> 05:37.000 What do you mean by a dirty job? 05:37.000 --> 05:48.000 Well, undesired jobs. Jobs that are hard, strenuous, dangerous, harmful, and lethal. 05:48.000 --> 05:54.000 What is an example of something like a dirty job that would be a lethal job? Something you've seen going on? 05:54.000 --> 06:08.000 Well, lethal is not yet in operation. This would be in the future. By that I mean jobs in hot environment, nuclear power plants and the like. 06:08.000 --> 06:19.000 But examples of undesired jobs is handling work pieces in hot environments. 06:19.000 --> 06:28.000 What about in assembly language control? Not control, but doing assembly processes? I know the Japanese have been very heavily involved in that. What's going on in just industrial use of robots? 06:28.000 --> 06:38.000 Well, that's the other kind of deadly job, the dehumanizingly dull jobs that are so common in a lot of our factories, and which Americans have demonstrated a strong dislike for. 06:38.000 --> 06:48.000 And it's the reason why a lot of our production is going offshore. And what's being done now, I think, in industry is that we're addressing those kinds of mundane assembly tasks, 06:48.000 --> 06:55.000 and taking the dehumanizing jobs and giving them to machines to free up human beings for more creative, more challenging kinds of work. 06:55.000 --> 07:02.000 Yeah, but you see, a very important point about assembly is that here the competition is very strong. 07:02.000 --> 07:18.000 Because to do assembly is a very complex task, especially if it's done in unstructured environments, not when pieces are jigged, if it's done like people. 07:18.000 --> 07:31.000 On the other hand, assembly people on assembly line, people working on assembly line, are paid very little. 07:31.000 --> 07:37.000 There are a lot of women that are working on assembly line, and they are underpaid. 07:37.000 --> 07:45.000 So it's a double-slam. On one hand, it's complex. On the other hand, you have to compete with very cheap labor. 07:45.000 --> 07:52.000 And the labor becomes even cheaper when it goes to Mexico or it goes to East Asia. So that's where the challenge is. 07:52.000 --> 08:07.000 On the other hand, with the undesired jobs like heat treatment or die casting or forging or arc welding, where the cost for the workers is high, 08:07.000 --> 08:14.000 and it's a very undesired job, and it's very easy to do, that's more cost-effective. 08:14.000 --> 08:22.000 I guess one of the differentiating factors in robots that are used, say, industrial in applications of that sort, 08:22.000 --> 08:27.000 that you can build a very precise robot that, say, would weld within a few millimeters of where it should weld, 08:27.000 --> 08:33.000 or you could use, say, vision processing to figure out where the object is and to manipulate it with very coarse mechanical devices. 08:33.000 --> 08:40.000 Or, as David points out, putting the robot into a structured environment, such as an integrated work cell, 08:40.000 --> 08:47.000 where the work is presented to the robot in such a way that it doesn't require the extreme accuracy or sensory capability 08:47.000 --> 08:51.000 that some of the anthropomorphic machines currently require. 08:51.000 --> 08:57.000 Henry Ford revolutionized American industry by bringing the work to the worker on the assembly line. 08:57.000 --> 09:03.000 And we see a very similar trend as a necessary part of the evolution of robotics in American industry, 09:03.000 --> 09:10.000 where we structure the workplace to suit the robot and make the robot easier to integrate into the overall scheme. 09:10.000 --> 09:12.000 And that's really applied robotics. 09:12.000 --> 09:18.000 It's a different set of problems than the technologies necessary to anthropomorphize machines, 09:18.000 --> 09:21.000 which is the basic research being done in robotics now. 09:21.000 --> 09:23.000 And I would like to make a very important point. 09:23.000 --> 09:29.000 I think it's an important point, and that is that people worry about unemployment and so on. 09:29.000 --> 09:34.000 I want to make an observation, which I think is important. 09:34.000 --> 09:45.000 The number of blue-collar workers that have been displaced or replaced so far by industrial robots is very, very small. 09:45.000 --> 09:51.000 And the projection, if we extrapolate from the past for the next five to 10 years, 09:51.000 --> 09:56.000 is also going to have a very small impact on the labor force. 09:56.000 --> 10:06.000 And my point is that I think the main reason for this is the fact that today's robots are not intelligent. 10:06.000 --> 10:11.000 They cannot compete effectively with human workers. 10:11.000 --> 10:17.000 Now, is that changing, though, with the applications, say, of artificial intelligence and, say, knowledge-based systems? 10:17.000 --> 10:19.000 Are those a factor in what's going on? 10:19.000 --> 10:23.000 Well, I think, as David points out, there's a whole spectrum of applications from the very simple, 10:23.000 --> 10:29.000 which are being handled by the very simple pick-and-place mechanical devices that, for example, 10:29.000 --> 10:33.000 the Japanese would call robots and we don't, to the very esoteric applications, 10:33.000 --> 10:38.000 which require lots of intelligence, lots of sensory capability. 10:38.000 --> 10:44.000 But there's a broad spectrum of applications somewhere in the middle where, if you select the application properly, 10:44.000 --> 10:51.000 then, in fact, the machine can be very cost-effective and very competitive with a minimal amount of intelligence. 10:51.000 --> 10:56.000 Ultimately, we will have to go to intelligent machines and distributed intelligence architectures, 10:56.000 --> 11:05.000 where the robotic elements in a totally automated factory would be in communication through several levels of computer hierarchy. 11:05.000 --> 11:11.000 Matt, you mentioned the Japanese, and the perception is that the Japanese are ahead of us in robotics, 11:11.000 --> 11:15.000 and you kind of pointed out a fine line in terms of defining what a robot is. 11:15.000 --> 11:19.000 What is your version of what's going on in terms of research in Japan and this country in robots? 11:19.000 --> 11:23.000 I would say that the Japanese are ahead of us in terms of automating their factories, 11:23.000 --> 11:30.000 and their way of automating the factories is a very systematic approach of looking at a factory as a unit of production 11:30.000 --> 11:34.000 and going in and solving the problem systematically from the bottom end up, 11:34.000 --> 11:37.000 looking for the easiest applications that they can resolve, 11:37.000 --> 11:41.000 learning in the process, and then moving on to the next most difficult applications. 11:41.000 --> 11:47.000 We see that as a very logical way of introducing automation into our factories. 11:47.000 --> 11:55.000 On the other hand, Americans are way ahead, I think, in terms of some of the technologies associated with the anthropomorphic machine. 11:55.000 --> 12:02.000 Certainly, vision systems, I think we have a lead over the Japanese and perhaps some of the other sensory areas. 12:02.000 --> 12:07.000 But it's becoming a world business, and FANUC Ltd., which is one of the leading manufacturers in Japan, 12:07.000 --> 12:11.000 has just signed a joint licensing agreement with General Motors. 12:11.000 --> 12:16.000 GMF is now going to be, if not already, the leading supplier of automation systems. 12:16.000 --> 12:21.000 Gentlemen, I have to interrupt because we're going to take a short break and then come back and meet two personal robots, 12:21.000 --> 12:25.000 Hiro from Heathkit and Teachmover from Microbot. That's coming up in just a moment. 12:31.000 --> 12:38.000 This is George Oliver, president of George L. Oliver Company, who distributes the Hiro One robot here in Northern California. 12:38.000 --> 12:43.000 George, maybe you could get Hiro to give us a basic demonstration of what it does. 12:43.000 --> 12:46.000 Sure. 13:14.000 --> 13:18.000 I have moved my arm. 13:24.000 --> 13:27.000 George, how much weight can that arm hold? 13:27.000 --> 13:32.000 It can hold about eight ounces extended and about a pound when it's fully retracted. 13:32.000 --> 13:35.000 And what kind of functional use could this arm perform? 13:35.000 --> 13:43.000 Oh, that arm could do things like pick up items from one assembly line and move them over to another. 13:44.000 --> 13:47.000 I have used my wrist. 13:48.000 --> 13:51.000 I have used my wrist. 13:51.000 --> 13:57.000 Does Hiro have the same normal axes of movement that an industrial robot might have? 13:57.000 --> 14:02.000 Yes, Hiro has six axes of motion like a class three industrial robot. 14:02.000 --> 14:05.000 And I am movable. 14:10.000 --> 14:15.000 I think I made an excellent decision. 14:15.000 --> 14:23.000 I think I made an excellent decision. I think I'll stay. 14:25.000 --> 14:27.000 Is he finished? 14:27.000 --> 14:29.000 I am here already. 14:29.000 --> 14:35.000 George, before we take his clothes off and see what's inside him, tell me, I see there's a keyboard and an LED display here. 14:35.000 --> 14:37.000 What do you do with that? 14:37.000 --> 14:39.000 Yes, this is used for data entry, Stu. 14:39.000 --> 14:44.000 And the LED display is to tell you where your information is stored within the computer. 14:44.000 --> 14:47.000 So you can program him through this keyboard. 14:47.000 --> 14:48.000 Yes. 14:48.000 --> 14:51.000 And I see you have a kind of breadboard here. What do you use that for? 14:51.000 --> 14:54.000 Yes, that can be used by students studying interfacing circuits. 14:54.000 --> 15:01.000 Okay, let's take his panels off and see if we can look inside Hiro and see what makes him tick, if that's what he does. 15:04.000 --> 15:08.000 Okay. I'll help you with the back one if you want to get the front one there. 15:08.000 --> 15:10.000 Yeah, that's easier. 15:10.000 --> 15:14.000 Okay, let's take a look at the front here, George, and what do we have over here? 15:14.000 --> 15:22.000 Okay, this is your main circuit board here with your microprocessor and all of the various ICs that interact with the other boards. 15:22.000 --> 15:24.000 Okay, can I spin them around here while we talk? 15:24.000 --> 15:30.000 Sure. Now, these various boards here are the sensor boards that operate with the various sensors again. 15:30.000 --> 15:34.000 This is the main drive control board. 15:34.000 --> 15:37.000 This one is the sonar transmitter and receiver board. 15:37.000 --> 15:44.000 And around here we have the sonar board and the main drive board. 15:44.000 --> 15:52.000 And around here we have the voice synthesis board and one of the other sensor boards here. 15:52.000 --> 15:56.000 Okay, and mainly you use Hiro as a training robot, as an educational robot, right? 15:56.000 --> 16:00.000 Yes, he's designed to be used by the student in the laboratory to study robotics. 16:00.000 --> 16:03.000 Okay, well, George, thanks so much. And now we'll go back to Gary. 16:03.000 --> 16:09.000 As Stuart joins us on the set, I'd like to introduce Dusty Rhodes and John Hill of Microbotics. 16:09.000 --> 16:12.000 Dusty, you have a device here that looks very interesting. Are you going to show us about that? 16:12.000 --> 16:21.000 We sure will. This is our TeachMover, which is a developmental robot used by industrial engineers to develop work cells in the factory, also for training engineers. 16:21.000 --> 16:25.000 Let me show you one of the little tricks and games it can play. 16:25.000 --> 16:35.000 This is the block stacking game. And it will find the large block and put it in the middle. 16:35.000 --> 16:39.000 The robot has a sensor that can sense how large the device is. 16:39.000 --> 16:45.000 And here it says, I have the large block. I'll put it in the middle. 16:45.000 --> 16:53.000 Now it knows to go back to the previous location for the smaller block and put it on top. 16:53.000 --> 16:58.000 I'll let it go on for just a moment and show what happens if it finds no block. 16:58.000 --> 17:02.000 Now oftentimes we go over and put the blocks in different places and try to fool it. 17:02.000 --> 17:08.000 But like a worker who's confused by instructions, if it looks for no block without work, it goes and sits down. 17:08.000 --> 17:15.000 During the setup for this, you had blocks placed around in various positions, and it wasn't able to find them. 17:15.000 --> 17:23.000 I assume that's because the sensing mechanism doesn't have any vision and so forth. Is that going to be added to this kind of device? 17:23.000 --> 17:29.000 That's true. John can talk about adding a vision to the work cell or the robot. 17:29.000 --> 17:36.000 Well, if a robot had a camera interface to it, such that the camera was looking down over the work area, 17:36.000 --> 17:45.000 the computer could process the image and locate the particular block and direct the robot to go there. That would be possible. 17:45.000 --> 17:48.000 In these instances, then, the robot could just automatically grab it. 17:48.000 --> 17:52.000 I know that David has worked with vision some. Do you have anything to add to that? 17:52.000 --> 17:56.000 Yeah, I agree with John. You could improve this by adding not just vision. 17:56.000 --> 18:04.000 You could have range and touch sensing, not just a micro switch like this robot has, but more an array of touch sensors. 18:04.000 --> 18:11.000 You could add some smarts into it so it knows what it is doing. If it makes an error, it will blow the whistle. 18:11.000 --> 18:15.000 David, where are we in adding smarts to robots? 18:15.000 --> 18:29.000 Well, we are struggling. Sensors are being added to robots today, and they are applied gradually in the industry. 18:29.000 --> 18:35.000 There are other applications of robots that would have to have sensors. These are unstructured environments, 18:35.000 --> 18:46.000 such as in the military or agriculture, medical institutions, etc., or home use, too. 18:46.000 --> 18:54.000 This is an area that is very difficult because robots are too dumb today to do this job, which requires a lot of intelligence. 18:54.000 --> 19:01.000 Do you see the field of personal robots growing as personal computers did, or robotics moving in the direction of computers? 19:01.000 --> 19:10.000 I put my bets more on the more application-oriented robots, such as I mentioned. 19:10.000 --> 19:16.000 The hobby is okay, but that is not where the big money would be, other than on a toy level. 19:16.000 --> 19:25.000 If you take a parallel with the popularity of microcomputers and personal computers, a lot of that was a grassroots effort. 19:25.000 --> 19:30.000 The invention of the Apple, for example, by Steve Wozniak, was a technical hobbyist's endeavor. 19:30.000 --> 19:36.000 It is kind of exciting to me to see robotics come through that grassroots evolution. 19:36.000 --> 19:41.000 I agree with you. I think it is wonderful. I think there is a good analogy between computers and robots. 19:41.000 --> 19:47.000 Just like computers started for commercial and scientific applications, now it is all over our lives. 19:47.000 --> 19:49.000 I think the same thing is going to happen with robots. 19:49.000 --> 19:53.000 I think it is a great idea that a lot of hobbyists are getting into, 19:53.000 --> 19:59.000 because there is a new generation now that would not be afraid of robots, 19:59.000 --> 20:04.000 that would be able to apply it in many areas of our lives. 20:04.000 --> 20:08.000 Something like this is relatively simple. It is an arm that can pick things up. 20:08.000 --> 20:14.000 You talked before about not only replacing blue-collar work with robots, but even white-collar work. How do you do that? 20:14.000 --> 20:23.000 You saw what Dusty was doing. He was using this teaching box to tell a robot what to do. 20:23.000 --> 20:31.000 If this information that he has in his head could be transferred into an automatic system, it could be done. 20:31.000 --> 20:39.000 Specifically, a computer-aided design database includes all the information that is needed to perform a certain job. 20:39.000 --> 20:47.000 We can eliminate the trainer that uses the teach pendant to move the robot and tell it what to do 20:47.000 --> 20:52.000 by using self-teaching and self-calibration, 20:52.000 --> 20:57.000 that all the information would be transferred to a computer, 20:57.000 --> 21:04.000 and the sensors would tell the robot where to find things and calibrate itself, and then do the job. 21:04.000 --> 21:07.000 Okay, Gary. Well, if you and I aren't replaced by robots, 21:07.000 --> 21:27.000 we'll be back here again next week for another edition of the Computer Chronicles. 21:38.000 --> 21:51.000 Micro Focus, creators of visual programming tools for software development, 21:51.000 --> 22:09.000 is pleased to provide major funding for the Computer Chronicles, the story of this continuing evolution. 22:22.000 --> 22:34.000 Random Access is made possible by a grant from Byte, the small systems journal, 22:34.000 --> 22:41.000 publishers of a monthly magazine on microcomputer technology and innovative projects in the world of computing. 22:41.000 --> 22:47.000 In the Random Access file this week, the TV news stories may all be about cabbage patch dolls, 22:47.000 --> 22:52.000 but the real hot Christmas gift this year is unquestionably the low-priced home computer. 22:52.000 --> 22:57.000 Analysts now say two and a half million computers will be under the Christmas tree this weekend, 22:57.000 --> 23:01.000 replacing last year's winner, video games, as the most popular Christmas present. 23:01.000 --> 23:07.000 And if industry figures are right, that will mean over a million computers thrown into the closet in just a few weeks, 23:07.000 --> 23:11.000 saturating even more the growing supply of used computers. 23:11.000 --> 23:16.000 That's leading to a fast-growing new business, computer swap meets and used computer stores. 23:16.000 --> 23:22.000 Computer Swap America, based in Palo Alto, will be expanding to five other cities across the country next year, 23:22.000 --> 23:26.000 and the Interstate Computer Bank, which used to sell used computers through the mail, 23:26.000 --> 23:30.000 has now opened up a storefront operation in Mountain View. 23:30.000 --> 23:34.000 Atari and Activision are hoping to pump some new life into the slumping video game business. 23:34.000 --> 23:41.000 The two largest video game suppliers announced this week a joint venture to distribute new video games via broadcast technology. 23:41.000 --> 23:48.000 They'll test out the new system early next year, and they say they hope to expand their service to include non-game software. 23:48.000 --> 23:55.000 Well, if Christmas 83 belongs to computers, the new year of 1984 may be called the year of the mouse. 23:55.000 --> 24:00.000 Analysts are saying the mouse business may grow to more than $10 million next year, 24:00.000 --> 24:05.000 and the consensus of opinion seems to be that the optical mouse will replace the mechanical mouse. 24:05.000 --> 24:09.000 One of the leaders in the field is Mouse Systems Corporation of Santa Clara. 24:09.000 --> 24:13.000 They expect to more than quadruple their business next year. 24:13.000 --> 24:16.000 1984 will certainly be the year of the semiconductor. 24:16.000 --> 24:21.000 Estimates are now that chip industry sales will grow by more than 30 percent next year. 24:21.000 --> 24:26.000 In fact, domestic orders in November hit an all-time high of $1 billion. 24:26.000 --> 24:30.000 Indeed, the stock market has turned the chip companies into their favorites this fall, 24:30.000 --> 24:33.000 after dumping on many other high-tech stocks. 24:33.000 --> 24:36.000 As the year ends, let's take a look at the year's big winners and losers. 24:36.000 --> 24:41.000 The winners were Intel, selling around $41 after hitting a low of $17 this year. 24:41.000 --> 24:46.000 National Semi, selling at nearly $16 after plunging to below $7 earlier in the year. 24:46.000 --> 24:50.000 Other strong finishers are Tandem and Genentech. 24:50.000 --> 24:56.000 On the losing side are Activision, selling near $4 after hitting nearly $13 earlier this year, 24:56.000 --> 25:00.000 and Eagle down below $9 after hitting nearly $25. 25:00.000 --> 25:07.000 Other losers were Apple, down considerably from its high, and Televideo, also near its yearly low. 25:07.000 --> 25:10.000 If you're into the stock market, don't throw away that computer. 25:10.000 --> 25:15.000 ValueLine has announced a new monthly software service called ValueScreen. 25:15.000 --> 25:19.000 For about $500 a year, ValueLine will send you a new disk every month, 25:19.000 --> 25:24.000 measuring 32 factors for each of some 1,600 common stocks. 25:24.000 --> 25:30.000 Program the disks to look for certain key criteria and have the computer recommend transactions. 25:30.000 --> 25:33.000 The Osborne Company is back, though in a very different form. 25:33.000 --> 25:39.000 Osborne's creditors have reportedly agreed to a reorganization under new president and CEO Ronald Brown. 25:39.000 --> 25:43.000 Osborne will get out of manufacturing, probably out of the domestic market, 25:43.000 --> 25:48.000 and will focus on its new IBM-compatible executive model. 25:48.000 --> 25:52.000 Rumors are flying over pending upgrades in the IBM PCjr. 25:52.000 --> 25:56.000 The Charm press has reportedly sent IBM back to the drawing boards. 25:56.000 --> 26:01.000 High on the list is an upgraded keyboard, after many complaints about the chiclet-style junior keyboard. 26:01.000 --> 26:06.000 There's also talk of adapting the junior to enable it to handle two disk drives. 26:06.000 --> 26:11.000 Apple finally made some progress this week in its battle to stop the trade in fake Apple computers. 26:11.000 --> 26:15.000 For a while, the problem of the fake Apples was thought to be limited to Southeast Asia, 26:15.000 --> 26:19.000 but the phony Apples have started showing up right here in California. 26:19.000 --> 26:26.000 U.S. Customs officials seized about 400 fake apples from computer dealers in San Francisco, Santa Ana, and Cupertino. 26:26.000 --> 26:28.000 Criminal charges are pending. 26:28.000 --> 26:33.000 We all know and use BASIC at one time or another, but do you know who wrote BASIC? 26:33.000 --> 26:40.000 Two Dartmouth professors, John Kemeny and Thomas Kurtz, and they hardly made a penny off one of the most widely used languages. 26:40.000 --> 26:48.000 Well, they're going to try again with a new language they call TrueBASIC, a supposedly universal BASIC that will run on almost all machines. 26:48.000 --> 26:50.000 It's due out late next year. 26:50.000 --> 26:58.000 And if you're into this kind of thing, you may get excited about knowing that the world's record was broken last week for factoring the largest number. 26:58.000 --> 27:06.000 A Cray-1 supercomputer in Albuquerque, New Mexico, factored a 67-digit number in just over 13 hours. 27:06.000 --> 27:08.000 The record had been a 50-digit number. 27:08.000 --> 27:17.000 There actually is a practical aspect of this, since many computer security systems are based on the supposed impossibility of factoring numbers of that size. 27:17.000 --> 27:22.000 Well, we often hear that one of the wonderful things about computers on the job is that they never call in sick. 27:22.000 --> 27:27.000 Well, one computer did this week in Sacramento after being shot at by two teenagers. 27:27.000 --> 27:31.000 The computer kept attendance records at a Sacramento high school. 27:31.000 --> 27:33.000 I guess the kids had cut too many classes. 27:33.000 --> 27:39.000 And a robot testified this week at a Casino Control Commission hearing in Atlantic City. 27:39.000 --> 27:44.000 A casino there wants to use the robot on the gambling floor to promote its entertainment shows. 27:44.000 --> 27:46.000 The robot said it was only one year old. 27:46.000 --> 27:51.000 The commission said the law prohibits minors from being on the gambling floor. 27:51.000 --> 27:54.000 Well, that's clearly enough from this week's Random Access File. 27:54.000 --> 28:00.000 We'll be off next week due to the holidays, but we'll see you again next year, immediately following the Computer Chronicles. 28:00.000 --> 28:02.000 I'm Stuart Shafaei. 28:02.000 --> 28:16.000 Random Access is made possible by a grant from Byte, the small systems journal, publishers of a monthly magazine on microcomputer technology and innovative projects in the world of computing.